Structure-adaptive image filtering using order statistics

In this article a structure-adaptive approach to the evaluation of image local properties for adaptive filtering is described. The adaptive procedure is based on selection of the most homogeneous neighborhood region from several possible structuring regions by the principle of maximum posterior probability. Then, an optimal evaluation of the pixel value at this point is performed involving pixels from the determined neighborhood region and the symmetric structuring region. The trimmed mean filters are used for the robust evaluation of local properties during estimation of object and background intensities when the supposed additive noise has a mixed conditional distribution, e.g., normal distribution with outliers. A time-efficient scheme for fast implementation of this method is proposed as well.